Biblio

Despite the abundance of information security guidelines, system developers have difficulties implementing technical solutions that are reasonably secure. Security patterns are one possible solution to help developers reuse security knowledge. The challenge is that it takes experts to develop security patterns. To address this challenge, we need a framework to identify and assess patterns and pattern application practices that are accessible to non-experts. In this paper, we narrowly define what we mean by patterns by focusing on requirements patterns and the considerations that may inform how we identify and validate patterns for knowledge reuse. We motivate this discussion using examples from the requirements pattern literature and theory in cognitive psychology.

Access policies are hard to express in existing programming languages. However, their accurate expression is a prerequisite for many of today's applications. We propose a new language that uses classes, first-class relationships, and first-class states to express access policies in a more declarative and fine-grained way than existing solutions allow.

Researchers interested in security often wish to introduce new primitives into a language. Extensible languages hold promise in such scenarios, but only if the extension mechanism is sufficiently safe and expressive. This paper describes several modifications to an extensible language motivated by end-to-end security concerns.

Very often in the software development life cycle, security is applied too late or important security aspects are overlooked. Although the use of security patterns is gaining popularity, the current state of security requirements patterns is such that there is not much in terms of a defining structure. To address this issue, we are working towards defining the important characteristics as well as the boundaries for security requirements patterns in order to make them more effective. By examining an existing general pattern format that describes how security patterns should be structured and comparing it to existing security requirements patterns, we are deriving characterizations and boundaries for security requirements patterns. From these attributes, we propose a defining format. We hope that these can reduce user effort in elicitation and specification of security requirements patterns.

Despite the abundance of information security guidelines, system developers have difficulties implementing technical solutions that are reasonably secure. Security patterns are one possible solution to help developers reuse security knowledge. The challenge is that it takes experts to develop security patterns. To address this challenge, we need a framework to identify and assess patterns and pattern application practices that are accessible to non-experts. In this paper, we narrowly define what we mean by patterns by focusing on requirements patterns and the considerations that may inform how we identify and validate patterns for knowledge reuse. We motivate this discussion using examples from the requirements pattern literature and theory in cognitive psychology.

An important step in achieving robustness to run-time faults is the ability to detect and repair problems when they arise in a running system. Effective fault detection and repair could be greatly enhanced by run-time fault diagnosis and localization, since it would allow the repair mechanisms to focus adaptation effort on the parts most in need of attention. In this paper we describe an approach to run-time fault diagnosis that combines architectural models with spectrum-based reasoning for multiple fault localization. Spectrum-based reasoning is a lightweight technique that takes a form of trace abstraction and produces a list (ordered by probability) of likely fault candidates. We show how this technique can be combined with architectural models to support run-time diagnosis that can (a) scale to modern distributed software systems; (b) accommodate the use of black-box components and proprietary infrastructure for which one has neither a specification nor source code; and (c) handle inherent uncertainty about the probable cause of a problem even in the face of transient faults and faults that arise only when certain combinations of system components interact. 

In our experience, exploratory testing has reached a level of maturity that makes it a practical and often the most cost-effective approach to testing. Notably, previous work has demonstrated that exploratory testing is capable of finding bugs even in well-tested systems [4, 17, 24, 23]. However, the number of bugs found gives little indication of the efficiency of a testing approach. To drive testing efficiency, this paper focuses on techniques for measuring and maximizing the coverage achieved by exploratory testing. In particular, this paper describes the design, implementation, and evaluation of Eta, a framework for exploratory testing of multithreaded components of a large-scale cluster management system at Google. For simple tests (with millions to billions of possible executions), Eta achieves complete coverage one to two orders of magnitude faster than random testing. For complex tests, Eta adopts a state space reduction technique to avoid the need to explore over 85% of executions and harnesses parallel processing to explore multiple test executions concurrently, achieving a throughput increase of up to 17.5×.